Modified 1D Virtual Force Field Approach to Moving Obstacle Avoidance for Autonomous Ground Vehicles
A modified 1D-virtual force field (1D-VFF) approach is newly proposed to effectively avoid moving obstacles for autonomous ground vehicle (AGV) applications. The underlying idea of this approach is to construct an obstacle force field based on the predicted trajectory of a moving obstacle. To do this, the time-to-collision and the probable area of collision are estimated using the obstacle position and velocity information measured from a FMCW radar. The predicted obstacle force field (POFF) replaces the obstacle force field (OFF) of the conventional 1D-VFF to enhance the AGV’s obstacle avoidance performance. As in the conventional 1D-VFF scheme, the steering force field (SFF) is generated by using the prescribed position of the goal and the current position of the ground vehicle. In order to ensure a collision-free local path against the moving obstacle, the steering command is determined as the maximizing solution of the integrated force field (IFF) defined by a linear combination of POFF and SFF. Simulations of various scenarios show that the proposed algorithm provides an improved local path planning performance against moving obstacles compared to the existing 1D-VFF methodology.
KeywordsAutonomous ground vehicle Collision avoidance Local path planning Moving obstacle Time-to-collision estimation Virtual force field
This work was supported in part by the National Research Foundation of Korea funded by the Ministry of Education (2016R1D1A3B03935616).
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